Yeasts

This is an example document for single cell data analysis using RamEx, replicating the results of the relevant analysis in RamEx: An R package for high-throughput microbial ramanome analyses with accurate quality assessment. bioRxiv

RamEx could be downloaded from [here] (https://github.com/qibebt-bioinfo/RamEx)

Test dataset could be download from ScienceDB

Load RamEx

library(RamEx)
library(dplyr)

Data Loading

plot(data)

 [1] "0h"   "2h"   "4h"   "8h"   "12h"  "20h"  "28h"  "36h"  "44h"  "52h"  "60h"  "68h"  "76h"  "84h"  "92h"  "100h"

Reductions

data.reduction <- Feature.Reduction.Pca(data[, data@wavenumber < 1700 | data@wavenumber > 2700], n_pc = 20) %>% Feature.Reduction.Umap(., min.dist = 0.5, n_neighbors = 50)

Phenotype analysis

clusters <- Phenotype.Analysis.Louvaincluster(data, resolutions = c(0.4), n_pc=20)

Creating the communities...
Processing resolution: 0.4 
Merging the isolate samples...

Plot.reductions(data.reduction, color=clusters$Resolution_0.4)

mean.spec(data$normalized.data, clusters$Resolution_0.4 , gap=0.3)

[1] "1" "2" "3" "4"

Plot.Distribution(data$group, clusters$Resolution_0.4 )

Raman markers

Plot.Heatmap.Markers(data, markers$markers_singular$wave)
Plot.Markers.Spectrum(object = data, markers=markers)

markers_population_cluster <- Raman.Markers.Correlations(data, group = clusters$Resolution_0.4, by_average = T, min.cor = 0.95, extract_num = FALSE,min.range = 20)

Finding singular markers ... 

Plot.Markers.Spectrum(data, markers_population_cluster)

MCR-ALS

mcr <- Spectral.Decomposition.Mcrals(data,n_comp = 2)
Plot.ViolinBox(mcr$concentration, data@meta.data$group)

Plot.ViolinBox(mcr$concentration, clusters$Resolution_0.4)

mean.spec(t(mcr$components), as.factor(colnames(mcr$components)), gap=0)

[1] "Comp 1" "Comp 2"

IRCA

IRCA_interests <- Intraramanome.Analysis.Irca.Global(data)

It may take a while to drawing the plot, please be patient.
It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

It may take a while to drawing the plot, please be patient.

band_ann <- data.frame(Wave_num=c(781,847,886,915,995,1075,1117,1148,1235,1295,1328,1438,1573,1591,1647,1738,2840,2900,2919),Group=c('Nucleic Acid','Polysaccharide','Polysaccharide','Polysaccharide','Protein','Lipids+Protein','Polysaccharide','Protein','Protein','Lipids','Protein','Lipids','Nucleic Acid','Lipids','Lipids','Lipids','Lipids','Lipids','Lipids'))
Intraramanome.Analysis.Irca.Local(data, bands_ann = band_ann)